Adaptive Sampling Strategies with Application to Water Resource Management

自适应采样策略在水资源管理中的应用

• 批准号: 0725441
• 负责人: Ali Sayed
• 金额: $ 32.99万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0725441&HistoricalAwards=false
• 关键词: Adaptive; Sampling; Strategies; Application; Water

ECCS-0725441SayedAdaptive Sampling Strategies with Application to Water Resource ManagementIntellectual Merit. Wireless sensor networks include both static and actuated devices and offer a promising solution for applications ranging from monitoring of diverse environmental phenomena to surveillance for national security. In many applications, these networks are deployed to monitor an underlying physical phenomenon over time and space, such as estimating a contaminant flux in water. Since the sensor devices operate unattended and with constrained energy reservoirs, energy efficiency becomes critical and directly determines the system lifetime. In order to achieve the simultaneous objectives of sensing fidelity and energy efficiency, it is necessary to develop strategies for selecting those sensor devices that contribute most effectively to the desired monitoring fidelity and to select other nodes for an inactive and low power standby state. The goals and intellectual merits of the proposed research are threefold: (i) to develop distributed methodologies to select a subset of sensor nodes and sensor measurement locations that can meet desired estimation accuracies; (ii) to test the developed methods experimentally; and (iii) to apply the methods to a critical application in water resource management such as accurately measuring contaminant flux in water.Broader Impact. The research has implications on the information technology infrastructure of the nation by enhancing the ability of wireless networks to sample and extract information from geographically scattered nodes subject to energy, communication, and time constraints. The research also addresses the demand for accurate sensing coverage in water resource management systems. And it helps train students in an area of fundamental relevance to future networking systems.

自适应采样策略及其在水资源管理中的应用。无线传感器网络包括静态和驱动设备，为从监测各种环境现象到监视国家安全等应用提供了有前途的解决方案。在许多应用中，这些网络用于监测随时间和空间变化的潜在物理现象，例如估计水中的污染物通量。由于传感器设备在无人值守的情况下运行，且能量存储受限，因此能源效率变得至关重要，并直接决定了系统的使用寿命。为了同时实现传感保真度和能源效率的目标，有必要制定策略，选择那些最有效地有助于所需的监测保真度的传感器设备，并选择其他节点处于非活动和低功耗待机状态。所提出的研究的目标和智力优点有三个方面：(i)开发分布式方法来选择能够满足所需估计精度的传感器节点和传感器测量位置子集；（二）对所制定的方法进行实验检验；（三）将这些方法应用于水资源管理中的关键应用，例如精确测量水中污染物通量。更广泛的影响。该研究通过提高无线网络从受能源、通信和时间限制的地理分散节点中采样和提取信息的能力，对国家的信息技术基础设施产生了影响。该研究还解决了水资源管理系统中对精确传感覆盖的需求。它还帮助学生在与未来网络系统相关的基础领域进行培训。